By Blossom Ukoha
Artificial intelligence is creating some of the fastest-growing and highest-paying opportunities in the global economy. But as the technology accelerates, another question is becoming harder to ignore: who is actually getting the opportunity to build, lead and profit from it?
The answer, according to new LinkedIn data, is still disproportionately men.
In the United States, women accounted for just 26 per cent of new hires into AI roles in 2025, compared with 50 per cent of hires into non-AI occupations. Across 27 countries, women held only 13 per cent of C-suite AI leadership positions at AI companies. Meanwhile, AI job postings have roughly doubled since 2023, with a typical listed salary of about $177,000, compared with $80,000 for non-AI roles.
That means the issue is no longer simply whether women have access to technology.
It is whether women will have a meaningful share of the economic power being created by it.
The Leadership Gap Is Already Visible
The imbalance does not begin in the C-suite. It develops along the entire career pipeline.
LinkedIn’s 2026 data shows that women represent 46 per cent of entry-level workers across the economies studied, but their representation falls to just 23 per cent at C-suite level. Women currently hold about 19 per cent of CEO roles, 27 per cent of CFO roles and 24 per cent of COO roles.
AI makes that existing leadership gap more consequential because the technology is not simply creating another category of jobs. It is reshaping how businesses operate, how decisions are made and where new economic value is created.
If women are missing from the leadership of that transformation, they risk being absent from some of the most influential business decisions of the next decade.
And the gap becomes even sharper when we look at the technical side of AI.
Who Is Building the Technology?
Women account for an average 44.8 per cent of data-annotator roles across the 19 economies analysed by LinkedIn, slightly above their 41.4 per cent representation in non-AI roles. But representation drops dramatically in roles closer to developing and deploying AI systems: women make up only 19.3 per cent of AI engineers and 20.6 per cent of machine-learning engineers.
This distinction matters.
Data annotation is important, it helps prepare and label the information used to train AI systems. But it is generally less specialised and lower-paid than engineering and model-development roles. LinkedIn’s research therefore reveals something deeper than a simple participation gap: women are not distributed evenly across the AI value chain.
The closer the work moves toward building the technology, the smaller women’s presence becomes.
And that has implications beyond salaries.
The people who build AI systems influence what problems those systems solve, what data they use, what risks they recognise and whose needs are considered during development.
The Entrepreneurial Opportunity Is Just as Important
AI is also changing entrepreneurship.
For a woman who once needed a large technical team to build a digital product, AI tools can reduce some of the barriers to experimentation, automation, research, content creation and product development.
But access to tools does not automatically create access to capital.
LinkedIn reports that women accounted for 28 per cent of founders in its 2026 Economic Graph data. At the same time, the share of founders with AI skills is growing faster among men: between 2019 and 2026, the proportion of male founders listing AI skills increased from 4.7 per cent to 15.2 per cent, while the proportion among female founders rose from 2.3 per cent to 9.1 per cent.
That widening skills gap matters because AI fluency is increasingly becoming part of the language of entrepreneurship.
The funding picture adds another layer.
PitchBook reports that US VC-backed companies with at least one female founder raised a record $73.6 billion in 2025, but AI accounted for roughly two-thirds of the capital invested in female-founded companies, with more than $30 billion coming from just Scale AI and Anthropic.
The headline figure therefore needs context: a small number of very large AI deals significantly influenced the total.
At the other end of the spectrum, all-female founding teams continue to receive only a small fraction of venture capital. Research tracking the global ecosystem has placed their share at around 2 per cent of VC funding.
The message is uncomfortable but important: women can be present in the entrepreneurial ecosystem while still being disproportionately absent from the capital required to scale.
And Then Comes the Disruption
There is another reason women’s position in AI deserves urgency.
Women are disproportionately represented in occupations that are more exposed to generative AI disruption. WEF analysis of LinkedIn data finds that women account for 57 per cent of workers in occupations most likely to be disrupted by generative AI, compared with 43 per cent of men.
This creates a troubling imbalance.
Women are more exposed to some of the disruption, yet less represented among the people building the technology, founding AI companies and occupying the executive positions determining how it is deployed.
The future cannot simply be about helping women adapt to AI after the decisions have been made. Women need to be part of making those decisions.
The Question Is Bigger Than Learning AI
AI education is important, but training alone will not solve this problem.
Companies must examine how they recruit for technical and leadership roles. Investors must look beyond familiar founder profiles when deciding who deserves capital. Universities and professional institutions must strengthen women’s pathways into engineering, data science and AI leadership.
And women themselves should not wait for AI to become “their field” before entering it.
Learn the tools. Understand the business models. Build with them. Invest in AI companies. Ask questions about AI governance. Move beyond using AI as a productivity assistant and learn how it can become part of a business strategy.
Most importantly, seek ownership and decision-making power, not merely participation.
The Future Should Not Be Built Without Her
AI is still young enough for its leadership structures to be shaped.
That makes this moment different.
The industry has not completely settled who will lead it, who will finance it or whose ideas will define its direction. There is still room to change the architecture.
But that window will not remain open indefinitely.
For businesses, the call is to build genuine pathways for women into technical roles, executive positions and AI decision-making.
For investors, it is to examine whether familiar networks are narrowing the pool of founders receiving capital.
For educators, it is to make AI and technical skills accessible to more girls and women before the career pipeline narrows.
And for women, the invitation is not simply to learn how to use AI.
Build with it. Lead with it. Invest in it. Question it. Govern it. Own a piece of what comes next.
Because the question facing women is no longer whether AI will change the future of business.
It will.
The question is whether women will be leading the businesses that AI creates—or merely adapting to the decisions others have already made.
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